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Feasible blocked multi-factor designs of unequal block sizes

Author

Listed:
  • Wang, Xiaodi
  • Chen, Xueping
  • Zhang, Yingshan

Abstract

A block design is called feasible if all the factor effects in it are estimable. This paper studies the design structures of feasible block designs when the block sizes are unequal. Based on a necessary and sufficient condition, we find two structure features which respectively lead to unfeasible and feasible designs. According to these results, an effective way to find feasible designs is provided.

Suggested Citation

  • Wang, Xiaodi & Chen, Xueping & Zhang, Yingshan, 2018. "Feasible blocked multi-factor designs of unequal block sizes," Statistics & Probability Letters, Elsevier, vol. 135(C), pages 102-109.
    • Handle: RePEc:eee:stapro:v:135:y:2018:i:c:p:102-109
    DOI: 10.1016/j.spl.2017.12.001
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    References listed on IDEAS

    as
    1. Xiaodi Wang & Yingshan Zhang, 2016. "General orthogonal designs for parameter estimation of ANOVA models under weighted sum-to-zero constraints," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(21), pages 6229-6244, November.
    2. Chen, Xue-Ping & Lin, Jin-Guan & Yang, Jian-Feng & Wang, Hong-Xia, 2015. "Construction of main-effect plans orthogonal through the block factor," Statistics & Probability Letters, Elsevier, vol. 106(C), pages 58-64.
    3. Ching-Shui Cheng & Pi-Wen Tsai, 2009. "Optimal two-level regular fractional factorial block and split-plot designs," Biometrika, Biometrika Trust, vol. 96(1), pages 83-93.
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